1. Technical Field
This invention relates to sensor networks of the kind in which data is collected from a network of mobile sensor devices, each of which is capable of taking measurements and relaying packets of data. Such devices are used by scientists taking measurements of the behavior of the environment. Mobile sensors are of particular application in monitoring the movement of individual objects such as vehicles or animals, and of fluid flows such as air, water, ice, lava, etc. However, they also have uses in measuring other, non-movement related, phenomena, because the mobility of the sensors avoids the researcher having to place them by hand, or the need for a fixed or uniform architecture. The properties to be measured may include temperature, pressure, or the chemical composition of the medium in which the sensors are carried. In some applications, the sensors may be attached to vehicles or other objects capable of autonomous movement. For example they may be attached to animals in order to monitor their migratory behavior or physiological condition, or to aircraft to monitor atmospheric conditions.
2. Related Art
The environments in which such devices are required to operate often have measurement points widely dispersed in both space and time. Some of the environments are hostile to human life. In some applications, such as the study of animal behaviour, human intervention could compromise the data. For these reasons the devices must be capable of operating autonomously, and transmitting the data they collect to a more convenient point using a wireless medium such as radio or sonar. Moreover it is not usually possible to provide a continuous power supply, so the useful life of a device is primarily constrained by battery life. A particular area where advantage would be seen would be in the application of pollution monitoring in rivers and reservoirs, or in the atmosphere. Here, again, it would be inconvenient to have to fix sensor devices to river beds or reservoir basins, or at monitoring points such as weather stations: it would be far easier to use floating devices. Such devices may also allow measurements at points where there is no solid surface, without the provision of buoys, tethered balloons, masts etc.
The sensors are each supplied with a wireless transmitter to transmit readings to a data collection point. The medium of the wireless transmissions may be radio, ultrasound or any other suitable means, depending on the environment in which the sensors are to be used.
Memory and processor capacity, and energy usage, are particularly important in sensor networks. These typically consist of very small, very cheap microprocessors, e.g., 16 bit, with 32 kilobytes of RAM. They also have a finite battery supply, which would be impractical to replace given the nature of the applications in which the sensors are to be used. It is therefore, very important that any communication protocol is energy-efficient, and also pared to a minimum in communication overhead and memory usage. The present applicant has developed a number of processes to develop an “ad hoc” wireless transmission network, in which the sensors relay data from one to another. This reduces the transmission power required overall, because two or more short-range transmissions require less power than a single transmission over the same total distance to the data collection point. (This is a consequence of the “inverse square law” of radiation propagation.) To avoid exhaustion of individual devices, these processes take into account the amount of traffic handled by each sensor device, and its remaining battery life, in order to determine how much relay traffic each device should be required to handle.
International patent applications PCT/GB2004/001999 (published as WO 2005/006668) and PCT/GB2004/003510 (published as WO 2005/025147) discuss this work. The first of these discloses a system of mobile data wireless relay devices, each having
receiving means for receiving payload data from a data source,
a buffer for storing payload data for subsequent transmission,
means for receiving status data from similar devices,
status data generation means for generating status data, the status data being derived from the quantity of data in the buffer store and the status data received from other devices, and comprising data relating to                the position of the device,        the quantity of data in the buffer store        a scalar forwarding value (δ) and        a forwarding direction,        
status transmitter means for transmitting status data to other devices
selection means for identifying from the status data a receiving device to which the payload data is to be forwarded, the receiving device being located in a position indicated by the forwarding direction,
payload transmission means for transmitting the payload data to the receiving device.
The other application discloses a system in which the data relay devices have
receiving means for receiving payload data from a data source,
a buffer for storing payload data for subsequent transmission,
means for receiving status data from similar devices,
status data generation means for generating status data, the status data being derived from the quantity of data in the buffer store and the status data received from other devices, and comprising data relating to                the separation of the device from other devices,        the quantity of data in the buffer store        
means for determining a scalar status value determined by the quantity of data stored in the buffer and its separation from nearby sensors,
status transmitter means for transmitting the status value to other devices
selection means for identifying, from the status data received from other devices, a receiving device having a status value which varies from its own status value in a manner indicative that payload data may be forwarded to it, and
payload transmission means for transmitting the payload data to the identified receiving device.
The wireless relay devices therefore identify the neighbouring device giving the best chance for the payload data to ultimately get all the way back to a data collection point or “sink”. It requires no explicit knowledge of the topology of the network, and in particular requires no details of any hop other than the one to which the device is directly connected.
These systems therefore allow the routing of data from sensor devices to higher-powered “sink” or “base-station” devices, using sensor/relay sensor devices that may be mobile in unpredictable ways, of low power, small, cheap and simple, and yet able to convey data back to a central network point or points in an opportunistic way, without prior configuration. In these systems the sensor/relay devices each have some buffer data storage capacity, which can be used either for data it has collected itself, or for data relayed from other devices. They co-operate to determine whether an individual device should transmit data to another such device. This decision is based on the amount of spare data capacity in each device, the distance between them (and therefore the transmission power required), the battery life remaining, and their relative proximities to the intended ultimate destination of the data (a data “sink”).
As has already been discussed, battery life is an important consideration in systems of this kind, as it would be impractical to locate or recover the devices in order to replenish their power supply when the batteries are exhausted. In addition to controlling the relaying of data between sensors as discussed in the patent specifications referred to above, it is desirable to find other ways to minimise power consumption in order to maximise the useful life of the devices. The present invention is concerned with improving the efficiency of the data collection process itself.
W B Heinzelman, A P Chandrakasan and H Balakrishnan, (Energy-Efficient Routing Protocols for Wireless Microsensor Networks, Proceedings of the 33rd International Conference on System Sciences (HICSS '00), January 2000) describe a process for routing data efficiently in sensor networks by exploiting distributed aggregation of data based on clustering techniques. Cluster heads are chosen in rotation to act as local aggregators and relays of data back to the central network point(s) (sink/base-station). Such aggregation of data can reduce communication load, and rotation of the heavy-duty function of relaying the data over long distances ensures that no one device is exhausted prematurely. However, there is a cost associated with maintaining these clusters and negotiating the next cluster head, which is viable for stationary sensor devices, but offers diminishing return as sensor devices become mobile.
This prior art arrangement is designed to maximise the data collected. However, in many situations, the contributions of individual items of data to the whole are not equal. A typical use of such sensors is for the detection of the time or location of a significant phenomenon within a much larger region of space and/or time monitored by the sensor network. For example, they may be used to detect the presence and dispersion of pollution in water. In such a situation, in order to provide useful data, the data points have to be spaced closely enough, in both space and time, to detect the phenomenon being measured. However, in many cases this results in the collection of a large amount of redundant data, collected in regions or at times when the phenomenon is not present, or has a constant value. This is because the distribution of the sensors is more or less random, and the time and location of the phenomenon is not knowable in advance. It is desirable to optimise the roles of sensing and routing in order to gather as much significant information from the sensor network as possible, within the constraints of the limited processing and communications capability, and the unpredictable movement of the sensors, which limit the amount of co-operation possible between the devices.
Work by A. Cerpa, J. Elson, D. Estrin, L. Girod, M. Hamilton and J. Zhao, refers to habitat monitoring as a driver for wireless communications technology, and focuses on power-saving by having devices switching themselves on and off according to whether they are in the vicinity of regions where interesting activity is expected, or detected by other devices. (“Habitat Monitoring: Application Driver for Wireless Communications Technology”, ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, Costa Rica, April 2001.) However, this process requires foreknowledge of where such activity is likely to take place,